Yes, unfortunately now it is not possible to install NEURON in the notebook as soon as it requires root privileges.
We will try to fix it somehow in the next release which should be in about two weeks from now.

But in case of NEST I don’t know how it is supposed to be installed. Is it a python package or something else.
I found this pagehttp://www.nest-simulator.org/installation/
If it is the installation process you can try to do the same from the notebook using !.

Another note. Don’t forget that at the moment notebooks are running on quite small VM and it is not supposed to be used to run code which require a lot of CPU/memory resources.

When pip installing Neuron one indeed needs root access (to install in /usr/)
But Neuron can also be installed as user, when compiled from source.
I’ve been trying to create a script for it yesterday, was almost there, but unfortunately half of it was lost when my iPython notebook was not saving itself when I guess the token expired (and didn’t tell me about it).

Since Neuron and NEST are such common tools used in the HBP, I think it should be part of the default install on these VMs. And yes, indeed, we shouldn’t use too much CPU, but this would just be for quick testing to see if the code works.

we are currently able to use NEST within the task framework by listing “bbp-hpc-2015.R2==0.0.0” among the task requirements, meaning that there is already a NEST version installed. I do not know if we can access this version from a notebook, can we?

In order to access PyNEST from within the notebooks by “import nest”, it is necessary to link NEST during installation to the available Python version. I guess that this should be done globally as described at the NEST installation page that you mentioned above:
When configuring NEST, one can use the flag --with-python and set the path to where PyNEST shall be put with --with-pynest-prefix=… to a location accessible in the search path PYTHONPATH.

Tasks and jupyter notebooks are running independently. So when you put “bbp-hpc-2015.R2==0.0.0” to task requirements it is a “hint” to task framework to load proper module before running a task in our cluster. Jupyter notebooks are running in another separate server which doesn’t have anything in common with the cluster. And the current situation is the NEST is not provided from the box in the jupyter notebook.

I have installed NEST with your example, but if I want to use some kinds of neurons (e.g. iaf_cond_exp) NEST throws an error:

> NESTError: UnknownModelName in Create_l_i: /iaf_cond_exp is not a known model name. Please check the modeldict for a list of available models. A frequent cause for this error is that NEST was compiled without the GNU Scientific Library, which is required for the conductance-based neuron models.

How can I install the GSL libraries?
I have tried the same approach as used for NEST, installing gsl-2.1, but it throws another error when I try to “make install” it.